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norbert2_sentiment_norec_8
This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5046
- Start: ------------------------------------------------------------
- Accuracy: 0.8
- Balanced Accuracy: 0.5
- F1 Score: 0.8889
- Recall: 1.0
- Precision: 0.8
- End: ------------------------------------------------------------
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Start | Accuracy | Balanced Accuracy | F1 Score | Recall | Precision | End |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.4534 | 1.0 | 5 | 0.6422 | ------------------------------------------------------------ | 0.8 | 0.5 | 0.8889 | 1.0 | 0.8 | ------------------------------------------------------------ |
| 0.5493 | 2.0 | 10 | 0.5159 | ------------------------------------------------------------ | 0.8 | 0.5 | 0.8889 | 1.0 | 0.8 | ------------------------------------------------------------ |
| 0.3452 | 3.0 | 15 | 0.5453 | ------------------------------------------------------------ | 0.8 | 0.5 | 0.8889 | 1.0 | 0.8 | ------------------------------------------------------------ |
| 0.2336 | 4.0 | 20 | 0.5046 | ------------------------------------------------------------ | 0.8 | 0.5 | 0.8889 | 1.0 | 0.8 | ------------------------------------------------------------ |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2
